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2: The History of AI

Ethics and Current Issues in Technology · LibreTexts

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    From LibreTexts, under CC BY-NC-SA 4.0, as the source states it; its equations are written in TeX, which the PDF shows typeset. This page at LibreTexts.

    • 2.1: The Early Foundations (Pre-1950s)
      This page examines humanity's quest to create artificial beings with human-like intelligence, reflecting on ancient myths and literary works like "Frankenstein" and "R.U.R." It discusses the implications of these narratives for consciousness and identity, leading to Alan Turing's pivotal contributions in the twentieth century, particularly the Turing Test. This progression lays the groundwork for the field of artificial intelligence.
    • 2.2: The Birth of AI (1950s – 1960s)
      This page discusses the Dartmouth Conference of 1956, a pivotal event in the founding of artificial intelligence, led by figures like John McCarthy and Marvin Minsky. It focused on exploring machines' abilities in language, problem-solving, and self-improvement. The subsequent years saw notable advances, such as the Logic Theorist and ELIZA, showcasing machines' reasoning and conversational skills.
    • 2.3: The AI Winters and Specialization (1970s – 1980s)
      This page explores the first "AI Winter" in the 1970s, characterized by disillusionment due to unmet expectations and challenges like the "combinatorial explosion." Critiques such as the Lighthill Report prompted funding reductions and a transition toward specialized tasks. This reflection led to the emergence of expert systems in the 1980s, highlighted by programs like MYCIN and DENDRAL.
    • 2.4: Machine Learning and the Data Revolution (1990s – 2000s)
      This page highlights the historic 1997 victory of IBM's Deep Blue over chess champion Garry Kasparov, illustrating the rise of artificial intelligence and its strategic potential. It marks a significant shift in AI development towards probabilistic and statistical methods, moving past rigid rule-based systems for greater adaptability. The increased availability of internet data and advancements in computation set the stage for substantial progress in AI during the upcoming decade.
    • 2.5: The Deep Learning Era (2010s)
      This page discusses the significant impact of AlexNet's introduction in 2012, which revolutionized AI and computer vision by reducing image classification errors and demonstrating deep learning's capabilities with vast datasets and GPUs. This advancement spurred investment in AI research and education.
    • 2.6: The Age of Generative AI (2020s – Present)
      This page discusses the transformative introduction of the Transformer architecture in 2017, which utilized attention mechanisms for advanced sequence modeling and simultaneous data processing. This innovation improved training efficiency and led to significant language models, including GPT-3 and BERT.

    2: The History of AI is shared under a CC BY-NC-SA 4.0 license and was authored, remixed, and/or curated by Dr. Marshal Miller - Northampton Community College.